An analytic and empirical focus. And all the possibilities in the world.
Our Master’s in Economics is an immersive, three-semester residential program that can be finished in as little as 12 months.
Over that short time, you’ll attain deep analytical and empirical skills in microeconomics and econometrics—essential, sought-after skills in the current market. We also provide dual-degree options, which can broaden opportunities.
months: complete the program in as little as one year
units to finish program
dual degree options
What You’ll Learn
- Microeconomic theory, including individual decision-making and market equilibrium, game theory and market design
- Empirical microeconomics, such as the use of econometric methods to understand markets, industries and other institutions
- Experimental and behavioral economics, including laboratory methods and approaches from psychology to understand individual and interactive decision making
You’ll be part of one of the premier institutions in the world in experimental economics, which includes the Economic Science Laboratory founded by Nobel laureate Vernon Smith. Our department also has substantial expertise in industrial organization, labor economics, economic history and environmental economics, all of which are data-intensive.
You’ll be required to take a set of core courses in microeconomics and econometrics, but may then take courses from a selection of Master’s-level electives to gain skills in empirical microeconomics and/or experimental and behavioral economics.
The Master's in Economics planned sequencing is:
ECON 510 Theory of Quantitative Methods in Economics
ECON 529 Mathematics for Economics
ECON 503A Microeconomic Theory I
ECON 503B Microeconomic Theory II
ECON 511A Econometrics I
ECON 5XX Elective 1
ECON 511B Econometrics II
ECON 5XX Elective 2
ECON 5XX Elective 3
ECON 5XX Elective 4
We will study various quantitative methods which provide background knowledge and tools for econometrics; i.e. empirical studies in economics. More specifically, we study probability theory, statistics, and practice using a statistical package R. The practical minimal goal is that you understand comfortably the first 3 chapters and Appendices 18.1 and 18.2 in Stock and Watson \Introduction to Econometrics" and use R confidently. In addition, we will study a script language called Python. Python is a general language with many libraries which make it a very useful tool to conducting quantitative analysis and used intensively in industry along with R. The goal here is to gain the understanding of the language to prepare you for a further study using Python. We will use R, a statistical package and a matrix language environment popular among statisticians, to enhance understanding of the concepts studied in class. There are excellent alternatives such as Stata. Although R is the de facto standard statistical software among statisticians, Stata may be more popular among economists. Once you are used to R, it does not take much effort to learn Stata.
Introduction to linear algebra, multivariable calculus, and optimization theory, with an emphasis on topics related to basic microeconomic and econometric theory. Designed primarily for entering masters students majoring in economics and related fields.
This course provides a rigorous foundation in Microeconomic Theory and its analytical methods at an advanced level that will prepare students for a corporate, regulatory, or consulting careers or for the pursuit of a PhD in Economics.
ECON 503B is a course in microeconomic theory at the masters level. The main focus of this course will be game theory. The main goal of the course is to give students an introduction into analyzing strategic interactions with self-interested agents. The course will introduce concepts for analyzing these games in different environments. Along with the concepts, a number of examples will be given, which highlight the applicability of game theory to a variety of fields, including economics, political science, computer science, biology, and engineering.
Econometrics is the art and science of the estimating and testing of economic models. These estimated models can then be used for causal inference and prediction. This course gives a rigorous introduction in econometrics. It covers the linear model, potential outcome model, the average treatment effect, multivariate linear model, nonlinear models with and without endogeneity, LASSO estimation, machine learning, prediction, and the bootstrap. Knowledge of statistics at the level of Economics 510 Masters level is assumed as well as knowledge of calculus at the level of Hansen (2018), appendix A. Computer programming experience is helpful but not required. An important objective of the course is for the student to learn how to conduct and how to critique empirical studies in economics and related fields. The course emphasizes understanding and intuition so that you can adjust the tools to new quantitative problems that you may encounter. This distinguishes the course from an undergraduate course or an 'econometric cookbook' course.
The objective of this course is to introduce the basic ideas of ¿modern¿ statistical learning and predictive modeling, from a statistical, theoretical and computational perspective, together with applications and analysis of economic data for graduate studies in economics and related fields.
Offered: Fall, Spring
This is an introductory course that covers the major results that have been obtained by using experiments in economics. Experiments are used in economics, like they are in the natural sciences and in psychology, to learn about the world around us. In the case of experimental economics, the goal is to better understand how people make decisions in economic settings and how these translate into overall market and group outcomes. The objectives of this course are to acquaint you with the main findings from economic experiments, give you experience participating in experiments, and show you how the insights can be used in business settings.
Offered: Fall, Spring
Use the tools from microeconomics and game theory to study the interaction of consumers, firms, industries, and governmental institutions. Focus on firms' strategic behaviors and how public policies create a balance between efficiency and market power.
Offered: Fall, Spring
This is a masters-level course in labor economics. In this course, we will explore the various determinants of individual and family decisions about labor force participation and hours worked, study the implications of taxes, welfare, and other social policies for the labor market, and discuss topics such as the minimum wage, inequality, immigration, and education. Students will be exposed to academic research in the field of labor economics and gain an understanding of the traditional economic models relevant to the study of the labor market.
Offered: Fall, Spring
This is a masters-level course in health economics. During this course, students will gain a solid foundation in four dimensions that are critical for a thorough understanding of this field: Theory, Institution, Policy, and Empirics.